Sensei Cyber Mentor
An AI cybersecurity mentor integrated with Blackfin OS tools.
Open source Open in the app JSON README (API)
About
An AI cybersecurity mentor integrated with Blackfin OS tools.
Details
- Kind
- Plugins
- Topic
- Security & identity
- Publisher
- mjcc30
- Origin
- gemini
- Category
- ferramentas
- Version
- 1.0.0
- Stars
- 2
- Last push
- 2025-12-04T19:41:11Z
- Repository state
- ativo
- Language
- Python
- License
- GPL-3.0
- Added
- 2026-08-30 14:13:39
- Updated
- 2026-08-30 14:13:39
- Origin id
mjcc30/sensei
README
# Sensei 🥋
### The AI Cyber Mentor for Hackers
**Sensei** is a CLI tool powered by Google Gemini, designed to assist penetration testers, CTF players, and cybersecurity students directly from their terminal.
## 🌟 Features
- **Context Aware:** Understands standard tools (Nmap, Metasploit, Burp).
- **Stealth & Ethics:** Warns about OpSec failures.
- **Terminal Beauty:** Rich markdown rendering.
- **Project Agnostic:** Works on any Linux distro (Kali, Blackfin, Ubuntu).
## 🚀 Installation
```bash
git clone https://github.com/mjcc30/sensei.git
cd sensei
uv sync
uv run main.py ask how do I scan for SMB vulnerabilities?
```
## 🤖 Usage
Set your API Key once:
```bash
export GEMINI_API_KEY="your_key_here"
```
**Quick Question:**
```bash
# No quotes needed!
uv run main.py ask how do I use nmap stealthily?
```
**Interactive Mode:**
```bash
uv run app/main.py chat
```
## 🔌 MCP Integration (Model Context Protocol)
Sensei exposes its tools (like Nmap) via a standard MCP Server. This allows other AI assistants (Claude Desktop, Gemini Advanced) to use Sensei's capabilities.
**Run the Server:**
```bash
uv run app/server.py
```
_(This starts a stdio JSON-RPC server)_
**Claude Desktop Configuration:**
Add this to your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"sensei": {
"command": "uv",
"args": ["run", "/path/to/sensei/app/server.py"]
}
}
}
```
## ⚙️ Configuration & Customization
Sensei uses a default persona ("Helpful Mentor"). You can customize or override these prompts (e.g., for specialized research or Red Teaming) by creating a `prompts.yaml` file.
1. Copy the example:
```bash
cp prompts.example.yaml prompts.yaml
```
2. Edit `prompts.yaml` to define your own System Prompts for each agent (Novice, Researcher, Master).
3. **Note:** `prompts.yaml` is ignored by Git to protect your custom methodology or sensitive instructions.
## 🔬 Architecture (v2 - The Swarm)
Sensei uses a **Multi-Agent Orchestrator**:
1. **Router:** Analyzes your query (Simple vs Complex).
2. **Specialists:** Delegates to the best agent (Novice, Researcher, or Master).
3. **A2A Bus:** Asynchronous internal communication.